Expectations induced by natural-like temporal fluctuations are independent of attention decrement: Evidence from behavior and early visual evoked potentials

Temporal expectations and attention decrement affect human behavior in opposing ways: the former positively, the latter negatively yet both exhibit similar neural signatures - i.e., reduction in the early event-related potential components' amplitude - despite different underlying mechanisms. Furthermore, there is a significant and growing debate in the literature regarding the putative role of attention in the encoding of expectations in perception. The question then arises as to what are the behavioral and neural consequences, if any, of attention decrement on temporal expectations and related enhancement of sensory information processing. Here, we investigated behavioral performance and visual N1a, N1p and P1 components during a sustained attention reaction time task inducing attention decrement under two conditions. In one condition, the inter-stimulus intervals (ISIs) were randomly distributed to impede expectation effects while for the other, the ISI exhibited natural-like long-term correlations supposed to induce temporal expectations. Behavioral results show that natural-like fluctuations in ISI indeed induced faster RT due to temporal expectations. These temporal expectations were beneficial even under attention decrement circumstances. Further, temporal expectations were associated with reduced N1a amplitude while attention decrement was associated with reduced N1p amplitude. Our findings provide evidence that the effects of temporal expectations and attention decrement induced in a single task can be independent at the behavioral level, and are supported at separate information processing stages at the neural level in vision.

[1]  N. Ramnani The primate cortico-cerebellar system: anatomy and function , 2006, Nature Reviews Neuroscience.

[2]  N. Rinehart,et al.  Interpersonal motor resonance in autism spectrum disorder: evidence against a global “mirror system” deficit , 2013, Front. Hum. Neurosci..

[3]  Gérard Dray,et al.  Towards a Near Infrared Spectroscopy-Based Estimation of Operator Attentional State , 2014, PloS one.

[4]  Bruce J. West,et al.  Maximizing information exchange between complex networks , 2008 .

[5]  Antigona Martínez,et al.  Source analysis of event-related cortical activity during visuo-spatial attention. , 2003, Cerebral cortex.

[6]  Kristina M. Visscher,et al.  The neural bases of momentary lapses in attention , 2006, Nature Neuroscience.

[7]  S. Perrey,et al.  Adaptations of motor neural structures' activity to lapses in attention. , 2015, Cerebral cortex.

[8]  A. Borst Seeing smells: imaging olfactory learning in bees , 1999, Nature Neuroscience.

[9]  C. Summerfield,et al.  Expectation (and attention) in visual cognition , 2009, Trends in Cognitive Sciences.

[10]  E. Vogel,et al.  The visual N1 component as an index of a discrimination process. , 2000, Psychophysiology.

[11]  A. Goldberger,et al.  Finite-size effects on long-range correlations: implications for analyzing DNA sequences. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[12]  Steven A. Hillyard,et al.  Identification of the neural sources of the pattern-reversal VEP , 2005, NeuroImage.

[13]  S Makeig,et al.  Functionally independent components of early event-related potentials in a visual spatial attention task. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[14]  D I Boomsma,et al.  Heritability of anterior and posterior visual N1. , 2007, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[15]  A. Nobre,et al.  Dissociating explicit timing from temporal expectation with fMRI , 2008, Current Opinion in Neurobiology.

[16]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[17]  O. Hikosaka,et al.  What and When: Parallel and Convergent Processing in Motor Control , 2000, The Journal of Neuroscience.

[18]  S. Eickhoff,et al.  Sustaining attention to simple tasks: a meta-analytic review of the neural mechanisms of vigilant attention. , 2013, Psychological bulletin.

[19]  A. Nobre,et al.  The hazards of time , 2007, Current Opinion in Neurobiology.

[20]  Donatella Spinelli,et al.  Impaired visual processing of contralesional stimuli in neglect patients: a visual-evoked potential study. , 2008, Brain : a journal of neurology.

[21]  Karl J. Friston The free-energy principle: a rough guide to the brain? , 2009, Trends in Cognitive Sciences.

[22]  G. Mangun,et al.  Covariations in ERP and PET measures of spatial selective attention in human extrastriate visual cortex , 1997, Human brain mapping.

[23]  Robert Oostenveld,et al.  FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..

[24]  Anna C. Nobre,et al.  Synergistic Effect of Combined Temporal and Spatial Expectations on Visual Attention , 2005, The Journal of Neuroscience.

[25]  A. Nobre,et al.  Where and When to Pay Attention: The Neural Systems for Directing Attention to Spatial Locations and to Time Intervals as Revealed by Both PET and fMRI , 1998, The Journal of Neuroscience.

[26]  Moritz Grosse-Wentrup,et al.  Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI , 2011, Comput. Intell. Neurosci..

[27]  Brigitte Röder,et al.  Attending points in time and space , 2006, Experimental Brain Research.

[28]  M. Meister,et al.  Dynamic predictive coding by the retina , 2005, Nature.

[29]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[30]  K. Lange Brain correlates of early auditory processing are attenuated by expectations for time and pitch , 2009, Brain and Cognition.

[31]  J. Muñoz-Ruata,et al.  Visual perception and frontal lobe in intellectual disabilities: a study with evoked potentials and neuropsychology. , 2010, Journal of intellectual disability research : JIDR.

[32]  R. Davies,et al.  Tests for Hurst effect , 1987 .

[33]  Leslie G. Ungerleider,et al.  Mechanisms of visual attention in the human cortex. , 2000, Annual review of neuroscience.

[34]  K. Lange The ups and downs of temporal orienting: a review of auditory temporal orienting studies and a model associating the heterogeneous findings on the auditory N1 with opposite effects of attention and prediction , 2013, Front. Hum. Neurosci..

[35]  S. Hillyard,et al.  Cortical sources of the early components of the visual evoked potential , 2002, Human brain mapping.

[36]  Pío Tudela,et al.  The attentional mechanism of temporal orienting: determinants and attributes , 2006, Experimental Brain Research.

[37]  Natasha M. Maurits,et al.  Mental Fatigue Affects Visual Selective Attention , 2012, PloS one.

[38]  S. Hillyard,et al.  Involvement of striate and extrastriate visual cortical areas in spatial attention , 1999, Nature Neuroscience.

[39]  A. Todorović,et al.  Repetition Suppression and Expectation Suppression Are Dissociable in Time in Early Auditory Evoked Fields , 2012, The Journal of Neuroscience.

[40]  C. Koch,et al.  Is perception discrete or continuous? , 2003, Trends in Cognitive Sciences.

[41]  M. Johns,et al.  A new method for measuring daytime sleepiness: the Epworth sleepiness scale. , 1991, Sleep.

[42]  R. C. Oldfield The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[43]  Bruce J. West,et al.  The Living Matter Way to exchange information. , 2010, Medical hypotheses.

[44]  Janneke F. M. Jehee,et al.  Attention Reverses the Effect of Prediction in Silencing Sensory Signals , 2011, Cerebral cortex.

[45]  S. Dehaene,et al.  Evidence for a hierarchy of predictions and prediction errors in human cortex , 2011, Proceedings of the National Academy of Sciences.

[46]  Donatella Spinelli,et al.  Hemispheric differences in VEPs to lateralised stimuli are a marker of recovery from neglect , 2013, Cortex.

[47]  E. Vogel,et al.  Sensory gain control (amplification) as a mechanism of selective attention: electrophysiological and neuroimaging evidence. , 1998, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[48]  Maarten A. S. Boksem,et al.  Effects of mental fatigue on attention: an ERP study. , 2005, Brain research. Cognitive brain research.

[49]  Timothy J. Gardner,et al.  Long-range Order in Canary Song , 2013, PLoS Comput. Biol..

[50]  Terrence J. Sejnowski,et al.  Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis , 2007, NeuroImage.

[51]  M. Shadlen,et al.  A representation of the hazard rate of elapsed time in macaque area LIP , 2005, Nature Neuroscience.

[52]  Bruce J. West,et al.  ON THE UBIQUITY OF 1/f NOISE , 1989 .

[53]  R. VanRullen,et al.  Spontaneous EEG oscillations reveal periodic sampling of visual attention , 2010, Proceedings of the National Academy of Sciences.

[54]  Susan A. Murphy,et al.  Monographs on statistics and applied probability , 1990 .

[55]  A. Nobre,et al.  Orienting attention in time. Modulation of brain potentials. , 1999, Brain : a journal of neurology.

[56]  H. Jasper Report of the committee on methods of clinical examination in electroencephalography , 1958 .

[57]  Jan Beran,et al.  Statistics for long-memory processes , 1994 .

[58]  K. Torre,et al.  Fractal analyses for 'short' time series: A re-assessment of classical methods , 2006 .

[59]  N. Kanwisher,et al.  Visual attention: Insights from brain imaging , 2000, Nature Reviews Neuroscience.

[60]  R. Chervin Epworth sleepiness scale? , 2003, Sleep medicine.

[61]  Bruce J. West,et al.  Habituation and 1/f-noise , 2010 .